Over the span of a generation, treasury organizations in many large companies have migrated from a reliance on spreadsheets toward the use of treasury management systems. These solutions provide measurable increases in cash visibility, productivity, and risk controls. Now new technologies like
data analytics, robotic process automation (RPA), and machine learning are rapidly building on these capabilities, fundamentally transforming the day-to-day activities of leading corporate treasury functions.

So extraordinary is the digital
transformation of treasury that
many believe treasury teams of the
future will primarily be engaged
in value-added activities in areas
like optimizing cash flows and
currency management, instead of
routine transactional tasks. Data-driven insights that staff acquire
from analytics tools will also be
increasingly valuable to other
parts of the enterprise.

Expectations are that withinfive years, most treasurymanagement systems will includeembedded RPA—which automatesrepetitive processing tasks usingrules-based logic. In fact, somevendors have already startedto integrate these technologies.

Algorithms in RPA tools can also
instantly highlight any variances
from expectations, illuminating
a path toward reconciling issues.
When RPA is further augmented
with data analytics, treasury can
develop more transparent and
precise forecasts of long-term
liquidity.

Within 10 years, treasury
platforms will “look and act like
no treasury management system
today,” says Bob Stark, vice
president of strategy at Kyriba, a
provider of a cloud-based treasury
management system.

Intensifying Pressures

The future may feel a bit scary
for treasury professionals, as
their roles will have to change.
But the consensus among many
treasury experts is that the
function is headed for its heyday.
Just in time, too, given the recent
regulatory upheaval increasing
the compliance obligations of
finance.